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  ## Dataset Description
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  - **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
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- - **Paper:** [TBA](TBA)
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  - **Point of Contact:** [Asahi Ushio](http://asahiushio.com/)
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  ### Dataset Summary
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  This is a subset of [QG-Bench](https://github.com/asahi417/lm-question-generation/blob/master/QG_BENCH.md#datasets), a unified question generation benchmark proposed in
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- ["Generative Language Models for Paragraph-Level Question Generation: A Unified Benchmark and Evaluation, EMNLP 2022 main conference"](paper_link).
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  This is [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) dataset for question generation (QG) task. The split
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  of train/development/test set follows the ["Neural Question Generation"](https://arxiv.org/abs/1705.00106) work and is
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  compatible with the [leader board](https://paperswithcode.com/sota/question-generation-on-squad11).
 
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  ## Dataset Description
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  - **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
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+ - **Paper:** [https://arxiv.org/abs/2210.03992](https://arxiv.org/abs/2210.03992)
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  - **Point of Contact:** [Asahi Ushio](http://asahiushio.com/)
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  ### Dataset Summary
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  This is a subset of [QG-Bench](https://github.com/asahi417/lm-question-generation/blob/master/QG_BENCH.md#datasets), a unified question generation benchmark proposed in
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+ ["Generative Language Models for Paragraph-Level Question Generation: A Unified Benchmark and Evaluation, EMNLP 2022 main conference"](https://arxiv.org/abs/2210.03992).
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  This is [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) dataset for question generation (QG) task. The split
23
  of train/development/test set follows the ["Neural Question Generation"](https://arxiv.org/abs/1705.00106) work and is
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  compatible with the [leader board](https://paperswithcode.com/sota/question-generation-on-squad11).